class_docstr: Randomly flip the input image and bbox left to right with a probability
  of p(0.5 by default).
  
  Parameters
  ----------
  p : float
      The probability to preceed with random cropping logic.
  
  Inputs:
      - **data**: input tensor with (Hi x Wi x C) shape.
      - **bbox**: input tensor with shape (N, 4+) where N is the number of bounding boxes.
          The second axis represents attributes of the bounding box.
          Specifically, these are :math:`(x_{min}, y_{min}, x_{max}, y_{max})`,
          we allow additional attributes other than coordinates, which stay intact
          during bounding box transformations.
  
  Outputs:
      - **out**: output tensor with same shape as `data`.
      - **bbox**: input tensor with same shape as `bbox`.
code: def _flip_bbox(self, img, bbox):
      width = img.shape[-2]
      xmax = width - bbox[:, 0]
      xmin = width - bbox[:, 2]
      bbox[:, 0] = xmin
      bbox[:, 2] = xmax
      return bbox
  
imports: import random
  from .......base import numeric_types
  from ......block import Block
  from .......util import is_np_array
  from .......None import ndarray, numpy_extension, numpy
  from .utils import _check_bbox_shape, bbox_crop, bbox_translate
  from .utils import bbox_resize, bbox_random_crop_with_constraints
label_desc: Use image node_id 4 for calling the ImageBboxRandomFlipLeftRight obj's underlying member method code with example usage: obj._flip_bbox(img, bbox) and returns: bbox